Global plans for exploratory missions aim at extending the distances travelled by humans well beyond low Earth orbit and establishing permanent bases on the surface of Moon and Mars [1]. This will inevitably lead to increasing mission duration, radiation intensity, gravity levels and degree of confinement and isolation to which the crews will be exposed. In this extended space mission context, the astronauts should have the means to collect medical/physiological data in...read more

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Global plans for exploratory missions aim at extending the distances travelled by humans well beyond low Earth orbit and establishing permanent bases on the surface of Moon and Mars [1]. This will inevitably lead to increasing mission duration, radiation intensity, gravity levels and degree of confinement and isolation to which the crews will be exposed. In this extended space mission context, the astronauts should have the means to collect medical/physiological data in order to understand if their physiological conditions are in nominal levels. The astronauts should be informed about possible diagnoses and get practical recommendations about treatment options in order to deal with medical issues with limited or no ground interactions. The mentioned scenario is possible if and only if the astronauts and medical crewmembers have access to an autonomous medical monitoring system with embedded diagnostic algorithms. AMIGO proposes to evaluate if and how data mining can be of benefit for an autonomous medical monitoring/diagnostic system. The following sections will present the target objectives, the definition of medical use cases, the development and validation of the proposed approach a short discussion will conclude this report.

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